The present embodiments relate to dose modeling. Dose levels are used for different types of therapy to treat cancer or other tumors. For example, radiation, laser, chemotherapy, or other therapies use different dose levels to treat (destroy or reduce) a tumor while minimizing the effects on healthy tissue.
The delivery of radiotherapy evolved from therapy designed based primarily on two dimensional x-ray images. Increasingly complex computer algorithms determine dose using three-dimensional x-ray based images. Advances in imaging technologies and the introduction of intensity modulated radiation therapy (IMRT) enable therapy planning with large amounts of data. In addition, greater awareness of the challenges to the accuracy of the treatment planning process, such as problems with set-error and organ movement, have begun to be systematically addressed. Four-Dimensional Radiotherapy or Image guided radiotherapy (IGRT) account for the tumor size and shape in therapy planning.
Image-guided radiation therapy is dependent on serial image datasets acquired using any of a variety of medical imaging platforms. Magnetic resonance imaging (MRI), computed tomography (CT), or ultrasound may be used. Other medical imaging includes functional imaging, such as positron emission tomography (PET). With PET, functional information can be correlated with anatomic localization from another modality, such as CT. As imaging datasets become more sophisticated, the therapy plan may account for the size and 3D and 4D positions of the target and normal structures. Real- or near-real-time positional re-planning of the radiation treatment localization coordinates may be provided. However, even with better position information, patients may still suffer normal tissue damage due to the therapy.
A malignant tumor is not a homogeneous mass, but is composed of regions that differ in tumor cell density, normal tissue involvement, vasculature, hypoxia, and gene expression. This biological heterogeneity results in large differences in the sensitivity of regions within the tumor to treatment with radiotherapy, chemotherapy, or new targeted agents. With non-invasive imaging and profiling, this intra-tumor heterogeneity may be identified. This has lead to the concept of “Biological Target Volume.” However assessing a link between images and the radio-sensitivity of different tissue regions (or voxels) is not straightforward. Because of the limited spatial resolution of imaging techniques (e.g., typically >1 mm3), it is uncertain whether the voxels around the tumor contain clonogenic cells. Moreover, the knowledge about how the different biological parameters influence radio-sensitivity on a voxel level is limited.